1 Initial Corpus generation

1.1 Corpus Creation

  1. Scopus download of documents retrieved from search string from Markard et al. (2012). Limited to LANGUAGE = ENGLISH AND TYPE = (ARTICLE).
  2. Selecting “seed” publications. 1% most cited per year. Ex-post manual exclusion. Results in 53 seed papers
  3. Retrieving for each seed 1000 publications with most shared references. Again, same limitations as in step 1.
  4. Adittional ex. post filtering. First, based on citations recieved and connectivity in bibliographic coupling network. Namely, I excluded edges in the bottom 10% quantile of the weight distribution (Jaccard weighted), also unconnected and nodes in the bottom 10% of the degree distribution. Lastly,after the community detection exercise, I excluded nodes in communities of less than 500 members.

That leads to an overall corpus size of:

## Number of unique publications in the final corpus:  9063

1.2 Seed Paper

In the following, we more in detail investigate the seed papers.

1.2.1 List of all seed papers

NEEDS UPDATE

1.2.2 Seep papers and corpus size

Generally, 50 x 1000 = 50.000 documents downloaded. However, due to an overlap of publications with most shared references to seed papers, final corpus is smaller.

First insight: It appears the main Sustainability corpus seems saturated, expansion appears more in adjacent fields.

2 General Overview over the ST and surrounding fields

2.1 Main Indicators: Publications, Authors, Countries

To start with, a general overview over the documents in the corpus

## 
## 
## MAIN INFORMATION ABOUT DATA
## 
##  Timespan                              1998 : 2020 
##  Sources (Journals, Books, etc)        1465 
##  Documents                             9063 
##  Average years from publication        7.58 
##  Average citations per documents       46.91 
##  Average citations per year per doc    4.702 
##  References                            475918 
##  
## DOCUMENT TYPES                     
##  article      9063 
##  
## DOCUMENT CONTENTS
##  Keywords Plus (ID)                    12999 
##  Author's Keywords (DE)                15440 
##  
## AUTHORS
##  Authors                               13661 
##  Author Appearances                    22719 
##  Authors of single-authored documents  1977 
##  Authors of multi-authored documents   11684 
##  
## AUTHORS COLLABORATION
##  Single-authored documents             2623 
##  Documents per Author                  0.663 
##  Authors per Document                  1.51 
##  Co-Authors per Documents              2.51 
##  Collaboration Index                   1.81 
##  
## 
## Annual Scientific Production
## 
##  Year    Articles
##     1998      100
##     1999      100
##     2000      122
##     2001      126
##     2002      133
##     2003      171
##     2004      178
##     2005      178
##     2006      235
##     2007      284
##     2008      312
##     2009      381
##     2010      459
##     2011      536
##     2012      621
##     2013      642
##     2014      686
##     2015      712
##     2016      697
##     2017      758
##     2018      762
##     2019      656
##     2020      214
## 
## Annual Percentage Growth Rate 3.5187 
## 
## 
## Most Productive Authors
## 
##    Authors        Articles   Authors        Articles Fractionalized
## 1  GEELS FW             53 GEELS FW                            31.5
## 2  HEKKERT MP           43 WONGLIMPIYARAT J                    21.5
## 3  SOVACOOL BK          37 LEYDESDORFF L                       20.3
## 4  TRUFFER B            35 SOVACOOL BK                         18.6
## 5  LEYDESDORFF L        34 NELSON RR                           15.0
## 6  RAVEN R              34 SMITH A                             14.5
## 7  FRANTZESKAKI N       33 HEKKERT MP                          13.7
## 8  BULKELEY H           32 BULKELEY H                          13.4
## 9  COENEN L             32 TRUFFER B                           13.2
## 10 SMITH A              32 KEMP R                              12.7
## 
## 
## Top manuscripts per citations
## 
##                          Paper            TC TCperYear
## 1  SHANE S, 2000, ACAD MANAGE REV       5320       253
## 2  ETZKOWITZ H, 2000, RES POLICY        2860       136
## 3  LAURSEN K, 2006, STRATEGIC MANAGE J  2654       177
## 4  ORLIKOWSKI WJ, 2000, ORGAN SCI       2425       115
## 5  BATHELT H, 2004, PROG HUM GEOGR      2393       141
## 6  GEELS FW, 2002, RES POLICY           2345       123
## 7  SHANE S, 2000, ORGAN SCI             2116       101
## 8  SARASVATHY SD, 2001, ACAD MANAGE REV 2058       103
## 9  BENNER MJ, 2003, ACAD MANAGE REV     2054       114
## 10 GEELS FW, 2007, RES POLICY           1841       132
## 
## 
## Corresponding Author's Countries
## 
##           Country Articles   Freq SCP MCP MCP_Ratio
## 1  UNITED KINGDOM     1168 0.1870 956 212     0.182
## 2  USA                 776 0.1243 654 122     0.157
## 3  NETHERLANDS         729 0.1167 552 177     0.243
## 4  GERMANY             432 0.0692 309 123     0.285
## 5  SWEDEN              336 0.0538 247  89     0.265
## 6  ITALY               269 0.0431 202  67     0.249
## 7  AUSTRALIA           235 0.0376 177  58     0.247
## 8  CANADA              235 0.0376 174  61     0.260
## 9  NORWAY              180 0.0288 141  39     0.217
## 10 DENMARK             178 0.0285 132  46     0.258
## 
## 
## SCP: Single Country Publications
## 
## MCP: Multiple Country Publications
## 
## 
## Total Citations per Country
## 
##      Country      Total Citations Average Article Citations
## 1  USA                      80302                    103.48
## 2  UNITED KINGDOM           75876                     64.96
## 3  NETHERLANDS              42815                     58.73
## 4  SWEDEN                   20253                     60.28
## 5  GERMANY                  19681                     45.56
## 6  CANADA                   14551                     61.92
## 7  ITALY                    11123                     41.35
## 8  DENMARK                   9556                     53.69
## 9  AUSTRALIA                 9555                     40.66
## 10 SPAIN                     7965                     50.73
## 
## 
## Most Relevant Sources
## 
##                                       Sources        Articles
## 1  ENERGY POLICY                                          424
## 2  RESEARCH POLICY                                        362
## 3  TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE            316
## 4  ENERGY RESEARCH AND SOCIAL SCIENCE                     260
## 5  JOURNAL OF CLEANER PRODUCTION                          228
## 6  SUSTAINABILITY (SWITZERLAND)                           214
## 7  ENVIRONMENTAL INNOVATION AND SOCIETAL TRANSITIONS      199
## 8  ECOLOGY AND SOCIETY                                    171
## 9  EUROPEAN PLANNING STUDIES                              164
## 10 TECHNOLOGY ANALYSIS AND STRATEGIC MANAGEMENT           150
## 
## 
## Most Relevant Keywords
## 
##     Author Keywords (DE)      Articles    Keywords-Plus (ID)     Articles
## 1  INNOVATION                      651 INNOVATION                    1688
## 2  SUSTAINABILITY                  375 SUSTAINABLE DEVELOPMENT        890
## 3  CLIMATE CHANGE                  348 SUSTAINABILITY                 867
## 4  GOVERNANCE                      309 CLIMATE CHANGE                 836
## 5  RENEWABLE ENERGY                270 ENERGY POLICY                  706
## 6  SUSTAINABILITY TRANSITIONS      220 GOVERNANCE APPROACH            649
## 7  RESILIENCE                      194 UNITED KINGDOM                 490
## 8  SUSTAINABLE DEVELOPMENT         163 TECHNOLOGICAL DEVELOPMENT      485
## 9  TRANSITION                      161 EUROPE                         452
## 10 ENERGY TRANSITION               158 DECISION MAKING                389

2.2 Cited references

Top 20 cited references:

2.3 Conceptual trajectories: Historical citation path analysis

## 
##  Legend
## 
##                                                                 Label Year LCS  GCS
## 1   KÖHLER J, 2019, ENVIRONMENTAL INNOVATION AND SOCIETAL TRANSITIONS 2019  33  122
## 2                                           SCHOT J, 2018, RES POLICY 2018  25  124
## 3                                           SCHOT J, 2018, RES POLICY 2018  23   46
## 4                                     LUEDERITZ C, 2017, J CLEAN PROD 2017  10  100
## 5                             AVELINO F, 2016, J ENVIRON POLICY PLANN 2016  43  122
## 6                             AVELINO F, 2016, J ENVIRON POLICY PLANN 2016  37   84
## 7                               SOVACOOL BK, 2016, ENERGY RES SOC SCI 2016  72  235
## 8                               SOVACOOL BK, 2016, ENERGY RES SOC SCI 2016  25   61
## 9   HANSEN T, 2015, ENVIRONMENTAL INNOVATION AND SOCIETAL TRANSITIONS 2015 110  219
## 10                                        MARKARD J, 2012, RES POLICY 2012 501 1029
## 11                                         COENEN L, 2012, RES POLICY 2012 227  469
## 12                                          TRUFFER B, 2012, REG STUD 2012 129  258
## 13                                 FASTENRATH S, 2018, SUSTAINABILITY 2018   2    5
## 14                                     EDMONDSON DL, 2019, RES POLICY 2019   3   26
## 15                             WIECZOREK AJ, 2018, ENVIRON SCI POLICY 2018  11   30
## 16                                  SCHLAILE MP, 2017, SUSTAINABILITY 2017   7   32
## 17 TORRENS J, 2019, ENVIRONMENTAL INNOVATION AND SOCIETAL TRANSITIONS 2019   2    4
## 18                                          RAKAS M, 2019, RES POLICY 2019   2    3
## 19                                 ROGGE KS, 2017, ENERGY RES SOC SCI 2017  21   68
## 20                                 ROGGE KS, 2017, ENERGY RES SOC SCI 2017  13   27
## 21                                           BINZ C, 2017, RES POLICY 2017  29   81
## 22                                   ZOLFAGHARIAN M, 2019, RES POLICY 2019   0    2
## 23 GRANDIN J, 2020, ENVIRONMENTAL INNOVATION AND SOCIETAL TRANSITIONS 2020   0    1
## 24                                      STRAMBACH S, 2020, RES POLICY 2020   0    1
## 25                                     TURNHEIM B, 2019, RES POLICY-a   NA  NA   NA
## 26                                PILLONI M, 2020, ENERGY RES SOC SCI 2020   0    2
## 27   GOYAL N, 2020, ENVIRONMENTAL INNOVATION AND SOCIETAL TRANSITIONS 2020   0    1
## IGRAPH 2b49041 DN-- 23 56 -- 
## + attr: name (v/c), id (v/c), size (v/n), years (v/n), color (e/c)
## + edges from 2b49041 (vertex names):
## [1] KÖHLER J, 2019, ENVIRONMENTAL INNOVATION AND SOCIETAL TRANSITIONS->ZOLFAGHARIAN M, 2019, RES POLICY                                  
## [2] KÖHLER J, 2019, ENVIRONMENTAL INNOVATION AND SOCIETAL TRANSITIONS->GRANDIN J, 2020, ENVIRONMENTAL INNOVATION AND SOCIETAL TRANSITIONS
## [3] KÖHLER J, 2019, ENVIRONMENTAL INNOVATION AND SOCIETAL TRANSITIONS->STRAMBACH S, 2020, RES POLICY                                     
## [4] SCHOT J, 2018, RES POLICY                                        ->GRANDIN J, 2020, ENVIRONMENTAL INNOVATION AND SOCIETAL TRANSITIONS
## [5] SCHOT J, 2018, RES POLICY                                        ->TURNHEIM B, 2019, RES POLICY-a                                    
## [6] LUEDERITZ C, 2017, J CLEAN PROD                                  ->KÖHLER J, 2019, ENVIRONMENTAL INNOVATION AND SOCIETAL TRANSITIONS 
## + ... omitted several edges

2.3.1 Authors, Themes & Journals

3 Topic modelling

I by now created some topic modelling. The results are now more fine-tuned, but there is still room for some improvement. We ran a LDA on the titles + abstracts of our corpus, aiming at identifying 10 topics (some different numbers of topics to generate shows that 10 result in good results, more topics lead to too much overlap between them)

3.1 Topics by topwords

This might still be finetuned, but initially doesnt look that bad I think. All the topics for me seem to be somewhat identifiable. We should maybe start naming them to make their interpretation later easier.

3.2 LDAViz

Here you find a nice way of exploring topics via the LDAVIz methodology of visulizing the result of an LDA. It dispolays all topics in a 2 dimensional TSNE (similar to PCA, but optimized for graphical illustration in 2d), and also gives a nice visual representation over the topics top-word distribution and overall frequencies of this words in the corpus. The \(\lambda\) parameter regulates the importance-ordering of the topwords. High \(\lambda\) order words by the highest propability to appear in the topic to the lowest (independent of the overall word popularity in the corpus), whle low \(\lambda\) emphasize words which are very specific to the topic, and rarely appear in others.

Play a bit around. Since it would be here a bit condensed, better check it out HERE in fullscreen for a better overview.